A method and system for image-based patient-specific guidance of cardiac arrhythmia therapies is disclosed. A patient-specific anatomical heart model is generated from medical image data of a patient. A patient-specific cardiac electrophysiology model is generated based on the patient-specific anatomical heart model and electrophysiology measurements of the patient. One or more virtual electrophysiological interventions are performed using the patient-specific cardiac electrophysiology model. One or more pacing targets or ablation targets based on the one or more virtual electrophysiological interventions are displayed.
Legal claims defining the scope of protection, as filed with the USPTO.
1. A method for patient-specific guidance of an electrophysiological intervention, comprising: generating a patient-specific anatomical heart model from medical image data of a patient; generating a patient-specific cardiac electrophysiology model based on the patient-specific anatomical heart model and electrophysiology measurements of the patient; performing one or more virtual electrophysiological interventions using the patient-specific cardiac electrophysiology model; displaying one or more pacing targets or ablation targets based on the one or more virtual electrophysiological interventions; and updating the patient-specific cardiac electrophysiology model based on results of the electrophysiological intervention.
2. The method of claim 1 , wherein updating the patient-specific cardiac electrophysiology model based on results of the electrophysiological intervention comprises: updating the patient-specific cardiac electrophysiology model based on results of an ablation performed in the electrophysiological intervention.
3. The method of claim 2 , wherein updating the patient-specific cardiac electrophysiology model based on results of an ablation performed in the electrophysiological intervention comprises: quantifying an ablated region of the patient's heart resulting from the ablation performed in the electrophysiological intervention; updating the patient-specific anatomical heart model to include the ablated region in the patient-specific anatomical heart model; and updating the patient-specific cardiac electrophysiology model based on the updated patient-specific anatomical heart model.
4. The method of claim 3 , wherein quantifying an ablated region of the patient's heart resulting from the ablation performed in the electrophysiological intervention comprises: segmenting a necrosis region in an interventional image acquired during the electrophysiological intervention.
5. The method of claim 4 , further comprising: personalizing a computational model of heat transfer and cellular necrosis for the patient based on a difference between the segmented necrosis region in the interventional image and a simulated necrosis region computed using the model of heat transfer and cellular necrosis.
6. The method of claim 3 , wherein quantifying an ablated region of the patient's heart resulting from the ablation performed in the electrophysiological intervention comprises: computing a necrosis region based on parameters of the ablation performed in the electrophysiological intervention using a patient-specific model of heat transfer and cellular necrosis personalized for the patient based on results of a previous ablation performed in the electrophysiological intervention.
7. The method of claim 2 , wherein the step of updating the patient-specific cardiac electrophysiology model based on results of an ablation performed in the electrophysiological intervention is performed in real-time during the electrophysiological intervention in response to the ablation performed in the electrophysiological intervention.
8. The method of claim 1 , wherein generating a patient-specific anatomical heart model from medical image data of a patient comprises: extracting a multi-component patient-specific heart morphology model from the medical image data and fusing the multi-component patient-specific heart morphology model into a single heart model; segmenting at least one of scar or border zone tissue in the medical image data mapping the segmented at least one of scar or border zone tissue to the single heart model; and generating a model of myocardium fiber architecture based on the single heart model.
9. The method of claim 1 , wherein generating a patient-specific cardiac electrophysiology model based on the patient-specific anatomical heart model and electrophysiology measurements of the patient comprises: registering the electrophysiology measurements of the patient to the patient-specific anatomical heart model; and estimating patient-specific parameters for the patient-specific cardiac electrophysiology model based on the registered electrophysiology measurements of the patient.
10. The method of claim 9 , wherein the electrophysiology measurements of the patient are invasive cardiac electrophysiology measurements acquired using a catheter probe and registering the electrophysiology measurements of the patient to the patient-specific anatomical heart model comprises: detecting a respective location of the catheter probe in each of a plurality of interventional images; calculating a transformation of electrophysiology measurements acquired by the catheter probe at each respective location to the patient-specific anatomical heart model based on the respective location of the catheter probe in each of the plurality of interventional images; and mapping a plurality of subsequent measurements by the catheter probe to the patient-specific anatomical heart model using the transformation.
11. The method of claim 9 , wherein the electrophysiology measurements of the patient are invasive cardiac electrophysiology measurements acquired using a catheter basket and registering the electrophysiology measurements of the patient to the patient-specific anatomical heart model comprises: calculating a transformation to register an interventional image acquired when the catheter basket is anchored in a heart of the patient to the patient-specific anatomical heart model; registering the catheter basket to the patient-specific anatomical heart model using the transformation; and mapping the cardiac electrophysiology measurements acquired by the catheter to the patient-specific anatomical heart model.
12. The method of claim 9 , wherein the electrophysiology measurements of the patient are body surface potential measurements of the patient and registering the electrophysiology measurements of the patient to the patient-specific anatomical heart model comprises: segmenting a torso model for the patient from the medical image data; registering the torso model to the patient-specific anatomical heart model; mapping the body surface potential measurements of the patient to the torso model; and back-projecting body surface potentials to the patient-specific anatomical heart.
13. The method of claim 1 , wherein the electrophysiology measurements of the patient include at least one of invasive cardiac electrophysiology mappings, ECG measurements, or body surface mappings (BSM).
14. The method of claim 1 , wherein generating a patient-specific cardiac electrophysiology model based on the patient-specific anatomical heart model and electrophysiology measurements of the patient comprises: estimating patient-specific electrical diffusivity and action potential duration parameters of the patient-specific cardiac electrophysiology model based on the patient-specific anatomical heart model and the electrophysiology measurements of the patient.
15. The method of claim 1 , wherein generating a patient-specific cardiac electrophysiology model based on the patient-specific anatomical heart model and electrophysiology measurements of the patient comprises: simulating cardiac electrophysiology in the patient-specific anatomical heart model using a computational cardiac electrophysiology model; and estimating patient-specific parameters of the cardiac electrophysiology model to minimize an error between the simulated cardiac electrophysiology and the electrophysiology measurements of the patient.
16. The method of claim 15 , wherein simulating cardiac electrophysiology in the patient-specific anatomical heart model using a computational cardiac electrophysiology model comprises: generating a Cartesian grid domain using the patient-specific anatomical heart model; and calculating transmembrane potential variation over time at each of a plurality of nodes of the patient-specific anatomical heart model in the Cartesian grid domain by computing a solution of the computational cardiac electrophysiology model for each of the plurality of nodes using a Lattice-Boltzmann method for electrophysiology.
17. The method of claim 15 , wherein the electrophysiology measurements of the patient are invasive cardiac electrophysiology measurements and estimating patient-specific parameters of the cardiac electrophysiology model to minimize an error between the simulated cardiac electrophysiology and the electrophysiology measurements of the patient comprises: estimating patient-specific parameters of the cardiac electrophysiology model that minimize an error between activation times of the simulated cardiac electrophysiology and activation times of the invasive cardiac electrophysiology measurements.
18. The method of claim 15 , wherein the electrophysiology measurements of the patient include body surface potential measurements and estimating patient-specific parameters of the cardiac electrophysiology model to reduce an error between the simulated cardiac electrophysiology and the electrophysiology measurements of the patient comprises: estimating patient-specific parameters of the cardiac electrophysiology model that reduce an error between the simulated cardiac electrophysiology and back-projected cardiac potentials calculated from the body surface measurements.
19. The method of claim 15 , wherein the electrophysiology measurements of the patient include body surface potential measurements and estimating patient-specific parameters of the cardiac electrophysiology model to reduce an error between the simulated cardiac electrophysiology and the electrophysiology measurements of the patient comprises: estimating patient-specific parameters of the cardiac electrophysiology model that reduce an error between simulated body surface potentials calculated from the simulated cardiac electrophysiology and the body surface potential measurements.
20. The method of claim 15 , wherein the estimating of the patient-specific parameters of the cardiac electrophysiology model to minimize the error between the simulated cardiac electrophysiology and the electrophysiology measurements of the patient is constrained by scar and border zone tissue in the patient-specific anatomical heart model.
21. The method of claim 15 , wherein estimating patient-specific parameters of the cardiac electrophysiology model to minimize an error between the simulated cardiac electrophysiology and the electrophysiology measurements of the patient comprises: estimating the patient-specific parameters of the patient-specific cardiac electrophysiology model and adjusting a location and size of at least one of scar or border zone tissue in the patient-specific anatomical heart model to minimize the error between the simulated cardiac electrophysiology and the electrophysiology measurements of the patient.
22. The method of claim 1 , wherein updating the patient-specific cardiac electrophysiology model based on results of the electrophysiological intervention comprises: updating the patient-specific cardiac electrophysiology model based on newly acquired electrophysiology measurements of the patient during the electrophysiological intervention.
23. The method of claim 1 , wherein generating a patient-specific cardiac electrophysiology model based on the patient-specific anatomical heart model and electrophysiology measurements of the patient comprises: estimating patient-specific parameters of the patient-specific cardiac electrophysiology model based on the electrophysiology measurements of the patient using a trained regression function.
24. The method of claim 1 , wherein performing one or more virtual electrophysiological interventions using the patient-specific cardiac electrophysiology model comprises: receiving user inputs selecting one or more pacing locations and one or more pacing protocols; performing a respective cardiac electrophysiology intervention simulation using the patient-specific cardiac electrophysiology model with a stimulus current added at the pacing location according to the pacing protocol for each of the pacing locations and pacing protocols; and displaying a visualization of the simulated cardiac electrophysiology resulting from each respective cardiac electrophysiology intervention simulation.
25. The method of claim 24 , wherein displaying a visualization of the simulated cardiac electrophysiology resulting from each respective cardiac electrophysiology intervention simulation comprises: displaying at least one of an ECG signal or an electrophysiology map calculated from each respective cardiac electrophysiology intervention simulation.
26. The method of claim 1 , wherein performing one or more virtual electrophysiological interventions using the patient-specific cardiac electrophysiology model comprises: automatically selecting a plurality of pacing locations and pacing protocols at which to perform virtual pacing; and performing a respective cardiac electrophysiology intervention simulation using the patient-specific cardiac electrophysiology model with a stimulus current added at the pacing location according to the pacing protocol for each of the plurality of pacing locations and pacing protocols.
27. The method of claim 26 , wherein performing one or more virtual electrophysiological interventions using the patient-specific cardiac electrophysiology model further comprises: automatically determining a target pacing location and pacing protocol based on the respective cardiac electrophysiology intervention simulations for the plurality of pacing locations and pacing protocols.
28. The method of claim 1 , wherein performing one or more virtual electrophysiological interventions using the patient-specific cardiac electrophysiology model comprises: receiving user inputs selecting one or more ablation locations and one or more ablation protocols; performing a respective cardiac electrophysiology intervention simulation using the patient-specific cardiac electrophysiology model for each of the ablation locations and ablation protocols; and displaying a visualization of the simulated cardiac electrophysiology resulting from each respective cardiac electrophysiology intervention simulation.
29. The method of claim 28 , wherein displaying a visualization of the simulated cardiac electrophysiology resulting from each respective cardiac electrophysiology intervention simulation comprises: displaying at least one of an ECG signal or an electrophysiology map calculated from each respective cardiac electrophysiology intervention simulation.
30. The method of claim 1 , wherein performing one or more virtual electrophysiological interventions using the patient-specific cardiac electrophysiology model comprises: a plurality of ablation locations and ablation protocols at which to perform virtual ablation; and performing a respective cardiac electrophysiology intervention simulation using the patient-specific cardiac electrophysiology model for each of the plurality of ablation locations and ablation protocols.
31. The method of claim 30 , wherein performing one or more virtual electrophysiological interventions using the patient-specific cardiac electrophysiology model further comprises: automatically determining a target ablation location and ablation protocol based on the respective cardiac electrophysiology intervention simulations for the plurality of ablation locations and ablation protocols.
32. The method of claim 1 , wherein performing one or more virtual electrophysiological interventions using the patient-specific cardiac electrophysiology model comprises: performing virtual pacing at a plurality of pacing locations and pacing protocols to determine a target pacing location and pacing protocol that induces a cardiac arrhythmia; and performing virtual ablation at a plurality of ablation locations and ablation protocols to determine a target ablation location and ablation protocol that treats the cardiac arrhythmia.
33. The method of claim 1 , wherein performing one or more virtual electrophysiological interventions using the patient-specific cardiac electrophysiology model comprises: performing virtual pacing at a plurality of pacing locations and pacing protocols to determine target pacing locations and pacing protocols for a cardiac resynchronization therapy.
34. The method of claim 1 , wherein displaying one or more pacing targets or ablation targets based on the one or more virtual electrophysiological interventions comprises: displaying the one or more pacing targets or ablation targets on a visualization of the patient-specific anatomical heart model.
35. The method of claim 1 , wherein displaying one or more pacing targets or ablation targets based on the one or more virtual electrophysiological interventions comprises: displaying the one or more pacing targets or ablation targets on an interventional image acquired during the electrophysiological intervention.
36. The method of claim 1 , wherein the patient-specific cardiac electrophysiology model is a patient-specific cardiac electromechanics model.
37. An apparatus for patient-specific guidance of an electrophysiological intervention, comprising: means for generating a patient-specific anatomical heart model from medical image data of a patient; means for generating a patient-specific cardiac electrophysiology model based on the patient-specific anatomical heart model and electrophysiology measurements of the patient; means for performing one or more virtual electrophysiological interventions using the patient-specific cardiac electrophysiology model; means for displaying one or more pacing targets or ablation targets based on the one or more virtual electrophysiological interventions; and means for updating the patient-specific cardiac electrophysiology model based on results of the electrophysiological intervention.
38. The apparatus of claim 37 , wherein the means for updating the patient-specific cardiac electrophysiology model based on results of the electrophysiological intervention comprises: means for updating the patient-specific cardiac electrophysiology model based on results of an ablation performed in the electrophysiological intervention.
39. The apparatus of claim 38 , wherein the means for updating the patient-specific cardiac electrophysiology model based on results of an ablation performed in the electrophysiological intervention comprises: means for quantifying an ablated region of the patient's heart resulting from the ablation performed in the electrophysiological intervention; means for updating the patient-specific anatomical heart model to include the ablated region in the patient-specific anatomical heart model; and means for updating the patient-specific cardiac electrophysiology model based on the updated patient-specific anatomical heart model.
40. The apparatus of claim 39 , wherein the means for quantifying an ablated region of the patient's heart resulting from the ablation performed in the electrophysiological intervention comprises: means for segmenting a necrosis region in an interventional image acquired during the electrophysiological intervention.
41. The apparatus of claim 40 , further comprising: means for personalizing a computational model of heat transfer and cellular necrosis for the patient based on a difference between the segmented necrosis region in the interventional image and a simulated necrosis region computed using the model of heat transfer and cellular necrosis.
42. The apparatus of claim 39 , wherein the means for quantifying an ablated region of the patient's heart resulting from the ablation performed in the electrophysiological intervention comprises: means for computing a necrosis region based on parameters of the ablation performed in the electrophysiological intervention using a patient-specific model of heat transfer and cellular necrosis personalized for the patient based on results of a previous ablation performed in the electrophysiological intervention.
43. The apparatus of claim 37 , wherein the means for generating a patient-specific anatomical heart model from medical image data of a patient comprises: means for extracting a multi-component patient-specific heart morphology model from the medical image data and fusing the multi-component patient-specific heart morphology model into a single heart model; means for segmenting at least one of scar or border zone tissue in the medical image data mapping the segmented at least one of scar or border zone tissue to the single heart model; and means for generating a model of myocardium fiber architecture based on the single heart model.
44. The apparatus of claim 37 , wherein the means for generating a patient-specific cardiac electrophysiology model based on the patient-specific anatomical heart model and electrophysiology measurements of the patient comprises: means for registering the electrophysiology measurements of the patient to the patient-specific anatomical heart model; means for estimating patient-specific parameters for the patient-specific cardiac electrophysiology model based on the registered electrophysiology measurements of the patient.
45. The apparatus of claim 37 , wherein the electrophysiology measurements of the patient include at least one of invasive cardiac electrophysiology mappings, ECG measurements, or body surface mappings (BSM).
46. The apparatus of claim 37 , wherein the means for generating a patient-specific cardiac electrophysiology model based on the patient-specific anatomical heart model and electrophysiology measurements of the patient comprises: means for simulating cardiac electrophysiology in the patient-specific anatomical heart model using a computational cardiac electrophysiology model; and means for estimating patient-specific parameters of the cardiac electrophysiology model to reduce an error between the simulated cardiac electrophysiology and the electrophysiology measurements of the patient.
47. The apparatus of claim 46 , wherein the means for generating a patient-specific cardiac electrophysiology model based on the patient-specific anatomical heart model and electrophysiology measurements of the patient comprises: means for estimating patient-specific electrical diffusivity and action potential duration parameters of the patient-specific cardiac electrophysiology model based on the patient-specific anatomical heart model and the electrophysiology measurements of the patient.
48. The apparatus of claim 37 , wherein the means for generating a patient-specific cardiac electrophysiology model based on the patient-specific anatomical heart model and electrophysiology measurements of the patient comprises: means for estimating patient-specific parameters of the patient-specific cardiac electrophysiology model based on the electrophysiology measurements of the patient using a trained regression function.
49. The apparatus of claim 37 , wherein the means for generating a patient-specific cardiac electrophysiology model based on the patient-specific anatomical heart model and electrophysiology measurements of the patient comprises: means for estimating patient-specific parameters of the patient-specific cardiac electrophysiology model and adjusting a location and size of at least one of scar or border zone tissue in the patient-specific anatomical heart model based on the electrophysiology measurements of the patient.
50. The apparatus of claim 37 , wherein the means for performing one or more virtual electrophysiological interventions using the patient-specific cardiac electrophysiology model comprises: means for performing virtual pacing at a plurality of pacing locations and pacing protocols to determine a target pacing location and pacing protocol that induces a cardiac arrhythmia; and means for performing virtual ablation at a plurality of ablation locations and ablation protocols to determine a target ablation location and ablation protocol that treats the cardiac arrhythmia.
51. The apparatus of claim 37 , wherein the means for performing one or more virtual electrophysiological interventions using the patient-specific cardiac electrophysiology model comprises: means for performing virtual pacing at a plurality of pacing locations and pacing protocols to determine target pacing locations and pacing protocols for a cardiac resynchronization therapy.
52. The apparatus of claim 37 , wherein the patient-specific cardiac electrophysiology model is a patient-specific cardiac electromechanics model.
53. A non-transitory computer readable medium storing computer program instructions for patient-specific guidance of an electrophysiological intervention, the computer program instructions defining operations comprising: generating a patient-specific anatomical heart model from medical image data of a patient; generating a patient-specific cardiac electrophysiology model based on the patient-specific anatomical heart model and electrophysiology measurements of the patient; performing one or more virtual electrophysiological interventions using the patient-specific cardiac electrophysiology model; displaying one or more pacing targets or ablation targets based on the one or more virtual electrophysiological interventions; and updating the patient-specific cardiac electrophysiology model based on results of the electrophysiological intervention.
54. The non-transitory computer readable medium of claim 53 , wherein updating the patient-specific cardiac electrophysiology model based on results of the electrophysiological intervention comprises: updating the patient-specific cardiac electrophysiology model based on results of an ablation performed in the electrophysiological intervention.
55. The non-transitory computer readable medium of claim 54 , wherein updating the patient-specific cardiac electrophysiology model based on results of an ablation performed in the electrophysiological intervention comprises: quantifying an ablated region of the patient's heart resulting from the ablation performed in the electrophysiological intervention; updating the patient-specific anatomical heart model to include the ablated region in the patient-specific anatomical heart model; and updating the patient-specific cardiac electrophysiology model based on the updated patient-specific anatomical heart model.
56. The non-transitory computer readable medium of claim 55 , wherein quantifying an ablated region of the patient's heart resulting from the ablation performed in the electrophysiological intervention comprises: segmenting a necrosis region in an interventional image acquired during the electrophysiological intervention.
57. The non-transitory computer readable medium of claim 56 , wherein the operations further comprise: personalizing a computational model of heat transfer and cellular necrosis for the patient based on a difference between the segmented necrosis region in the interventional image and a simulated necrosis region computed using the model of heat transfer and cellular necrosis.
58. The non-transitory computer readable medium of claim 55 , wherein quantifying an ablated region of the patient's heart resulting from the ablation performed in the electrophysiological intervention comprises: computing a necrosis region based on parameters of the ablation performed in the electrophysiological intervention using a patient-specific model of heat transfer and cellular necrosis personalized for the patient based on results of a previous ablation performed in the electrophysiological intervention.
59. The non-transitory computer readable medium of claim 53 , wherein generating a patient-specific anatomical heart model from medical image data of a patient comprises: extracting a multi-component patient-specific heart morphology model from the medical image data and fusing the multi-component patient-specific heart morphology model into a single heart model; segmenting at least one of scar or border zone tissue in the medical image data mapping the segmented at least one of scar or border zone tissue to the single heart model; and generating a model of myocardium fiber architecture based on the single heart model.
60. The non-transitory computer readable medium of claim 53 , wherein generating a patient-specific cardiac electrophysiology model based on the patient-specific anatomical heart model and electrophysiology measurements of the patient comprises: registering the electrophysiology measurements of the patient to the patient-specific anatomical heart model; estimating patient-specific parameters for the patient-specific cardiac electrophysiology model based on the registered electrophysiology measurements of the patient.
61. The non-transitory computer readable medium of claim 53 , wherein the electrophysiology measurements of the patient include at least one of invasive cardiac electrophysiology mappings, ECG measurements, or body surface mappings (BSM).
62. The non-transitory computer readable medium of claim 53 , wherein generating a patient-specific cardiac electrophysiology model based on the patient-specific anatomical heart model and electrophysiology measurements of the patient comprises: estimating patient-specific electrical diffusivity and action potential duration parameters of the patient-specific cardiac electrophysiology model based on the patient-specific anatomical heart model and the electrophysiology measurements of the patient.
63. The non-transitory computer readable medium of claim 53 , wherein generating a patient-specific cardiac electrophysiology model based on the patient-specific anatomical heart model and electrophysiology measurements of the patient comprises: simulating cardiac electrophysiology in the patient-specific anatomical heart model using a computational cardiac electrophysiology model; and estimating patient-specific parameters of the cardiac electrophysiology model to reduce an error between the simulated cardiac electrophysiology and the electrophysiology measurements of the patient.
64. The non-transitory computer readable medium of claim 53 , wherein generating a patient-specific cardiac electrophysiology model based on the patient-specific anatomical heart model and electrophysiology measurements of the patient comprises: estimating patient-specific parameters of the patient-specific cardiac electrophysiology model based on the electrophysiology measurements of the patient using a trained regression function.
65. The non-transitory computer readable medium of claim 53 , wherein generating a patient-specific cardiac electrophysiology model based on the patient-specific anatomical heart model and electrophysiology measurements of the patient comprises: estimating patient-specific parameters of the patient-specific cardiac electrophysiology model and adjusting a location and size of at least one of scar or border zone tissue in the patient-specific anatomical heart model based on the electrophysiology measurements of the patient.
66. The non-transitory computer readable medium of claim 53 , wherein performing one or more virtual electrophysiological interventions using the patient-specific cardiac electrophysiology model comprises: performing virtual pacing at a plurality of pacing locations and pacing protocols to determine a target pacing location and pacing protocol that induces a cardiac arrhythmia; and performing virtual ablation at a plurality of ablation locations and ablation protocols to determine a target ablation location and ablation protocol that treats the cardiac arrhythmia.
67. The non-transitory computer readable medium of claim 53 , wherein performing one or more virtual electrophysiological interventions using the patient-specific cardiac electrophysiology model comprises: performing virtual pacing at a plurality of pacing locations and pacing protocols to determine target pacing locations and pacing protocols for a cardiac resynchronization therapy.
68. The non-transitory computer readable medium of claim 53 , wherein displaying one or more pacing targets or ablation targets based on the one or more virtual electrophysiological interventions comprises: displaying the one or more pacing targets or ablation targets on a visualization of the patient-specific anatomical heart model.
69. The non-transitory computer readable medium of claim 53 , wherein displaying one or more pacing targets or ablation targets based on the one or more virtual electrophysiological interventions comprises: displaying the one or more pacing targets or ablation targets on an interventional image acquired during the electrophysiological intervention.
70. The non-transitory computer readable medium of claim 53 , wherein the patient-specific cardiac electrophysiology model is a patient-specific cardiac electromechanics model.
Cooperative Patent Classification codes for this invention. Click any code to explore related patents in that topic.
April 10, 2015
May 21, 2019
Browse 5M+ US patents with plain-English claim translations and AI-generated analysis.